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Erschienen in: Reproductive Biology and Endocrinology 1/2018

Open Access 01.12.2018 | Review

Human sperm acrosome function assays are predictive of fertilization rate in vitro: a retrospective cohort study and meta-analysis

verfasst von: Fang Xu, Ganggang Guo, Wenbing Zhu, Liqing Fan

Erschienen in: Reproductive Biology and Endocrinology | Ausgabe 1/2018

Abstract

Objective

To determine whether acrosome function scoring—including acrosomal enzyme (AE) levels and acrosome reaction (AR) results—can predict fertilization rate in vitro.

Methods

We examined the predictive value of acrosomal enzymes (AE) determined by spectrophotometry/N-α-benzoyl-dl-arginine-p-nitroanilide for fertilization rate (FR) in vitro in a retrospective cohort study of 737 infertile couples undergoing IVF therapy. Additionally, a meta-analysis was done for prospective cohort or case-control studies; the following summary measures were reported to expand upon the findings: pooled spearman correlation coefficient (Rs), standardized mean difference (SMD), sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score (DS), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (AUC).

Results

Lower AE levels determined by spectrophotometry with a cut-off value of <25μIU/106 spermatozoa were predictive of total fertilization failure (TFF) with moderate SEN (88.23%) and low SPE (16.50%). On meta-analysis, a total of 44 unique articles were selected, but given the multiple techniques described there was a total of 67 total datasets extracted from these 44 articles, comprising 5356 infertile couples undergoing IVF therapy. The AE levels or induced AR% was positively correlated with FR (Rs = 0.38, SMD = 0.79; Rs = 0.40, SMD = 0.86, respectively). Lower AE levels or induced AR% was predictive of lower fertilization rate with moderate accuracy (AUC = 0.78, AUC = 0.84, respectively); this was accompanied by low SEN/moderate SPE (0.57/0.85), moderate SEN/moderate SPE (0.79/0.87), respectively. For AE assay, the diagnostic performance in Asia (Rs = 0.24, SMD = 0.50) was inferior to that in North America (Rs = 0.54, SMD = 0.81) and Europe (Rs = 0.46, SMD = 0.92). Cryopreserved spermatozoa (SMD = 0.20, P = 0.204) were inferior to fresh spermatozoa (SMD = 0.89, P <  0.001). Sperm preparation yielded inferior results as compared to no preparation; spermatozoa after swim up were weak relevant (Rs = 0.27, P = 0.044); and there was no correlation for spermatozoa after a discontinuous gradient (SMD = 1.07, P >  0.05). Lower AE levels determined by fluorometry or substrate assay were used for predicting lower FR with low sensitivity and high specificity; the spectrophotometry assay had an uncertain predictive value. For induced AR assay, the diagnostic performance in the other areas was inferior to that in Africa (Rs = 0.65, SMD = 1.86). No preparation or double preparation yielded inferior results as compared to one preparation (Rs = 0.41); discontinuous gradient (Rs = 0.17, SMD = 0.47) was inferior to swim up (Rs =0.65, SMD = 1.51). Nonphysiological triggers (SMD = 0.81) did not differ from physiological triggers (SMD = 0.95) in general; ZP (Rs = 0.63) or mannose (Rs = 0.59) was superior to other physiological or nonphysiological triggers; and there was no correlation for human follicle fluid, progesterone, cyclic adenosine 3′-5′-phosphate analogue and phorbol ester–BSA-GlcNAc Neoglycoproteins with N-acetylglucosamine residues. Lower induced AR% determined by indirect immunofluorescence, direct immunofluorescence with lection, or triple stain was used for predicting lower FR, with moderate sensitivity/high specificity, moderate sensitivity/high specificity, or high sensitivity/low specificity.

Conclusions

Although the correlation between acrosome function scoring and FR was significant, the assays were neither highly sensitive nor specific. Additionally, the diagnostic performance showed regional effects as well as an effect of the sperm preparation or assay method. More studies of multicenter, large-scale, careful design and synthesizing multiple sperm functional assays and oocyte quality assays are still needed in clinical settings to better predict fertilization outcome in IVF.
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12958-018-0398-y) contains supplementary material, which is available to authorized users.
Abkürzungen
AE
Acrosomal enzyme
AUC
Area under the summary receiver operating characteristic curve
BAEE
N-benzoyl-l-arginine ethyl ester
BAPNA
N-α-benzoyl-dl-arginine-p-nitroanilide
BSA-GlcNAc
Neoglycoproteins with N-acetylglucosamine residues
CAMP
Cyclic adenosine 3′-5′-phosphate analogue
CI
Confidence interval
DBM
Dyes for bright-field microscopy
DOR
Diagnostic odds ratio
DS
Diagnostic score
FITC-Con A
Concanavalin A lectin
FITC-GB24
Fluorescein isothiocyanate-GB24
FITC-PNA
Fluorescein isothiocyanate-conjugated peanut agglutinin
FITC-PSA
Fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm
FR
Fertilization rate
HFF
Human follicle fluid
ICSI
Intracytoplasmic sperm injection
IVF
in vitro fertilization
mAb 4D4-proacrosin
Monoclonal anti-proacrosin antibody
NLR
Negative likelihood ratio
P
Progesterone
pAb-acrosin
Polyclonal anti-acrosin antibody
pAb-hyaluronidase
Polyclonal anti-hyaluronidase antibody
PLR
Positive likelihood ratio
RIA
Radioimmunoassay
RITC-PSA
Rhodamine-conjugated Pisurn sativum agglutimm
RR
Risk ratio
Rs
Spearman correlation coefficient
SEN
Sensitivity
SMD
Standardized mean difference
SPE
Specificity
SROC
Summary receiver operating characteristic
TEM
Transmission electron microscopy
TFF
Total fertilization failure
TPA
Phorbol ester
TRITC-PSA
Tetramethylrhodamine-conjugated PSA
ZP
Zona pellucida

Background

The sperm acrosome is a Golgi complex-derived flat granule overlaying the anterior two-thirds of the sperm head and contains numerous acrosomal enzymes (AEs) such as protease, glycosidase, acrosin, hyaluronidase, and high-electron density semisolid matrix proteins. Among AEs, the serine proteinase acrosin and hyaluronidase are of particular interest owing to their roles in fertilization, which include limited proteolysis of zona proteins to facilitate spermatozoa penetration into the various layers of the ovum. Acrosin—which is exclusive to the acrosome of mammalian spermatozoa—is mainly synthesized and stored in an enzymatically inactive zymogen form (i.e., proacrosin), and is released during acrosomal exocytosis following maturation [1]. Hyaluronidase is secreted and depolymerizes the matrix between cells of the cumulus oophorus [2].
Intact acrosome function—containing adequate active AEs (proacrosin, acrosin, and hyaluronidase) and ability to undergo acrosome reaction (AR) after the induction—is necessary for sperm fertility. The detection of acrosome function can provide insight into the fertilizing capacity of spermatozoa, and is therefore considered a useful diagnostic tool for male infertility. Several methods have been described to assay AE, including fluorometry, western blotting, spectrophotometry, substrate assays, and radioimmunoassay (RIA). For the indirect fluorometry, polyclonal anti-acrosin (pAb-acrosin) [3] or anti-hyaluronidase (pAb-hyaluronidase) antibodies [3] or a monoclonal anti-proacrosin antibody (mAb 4D4-proacrosin) [4] is used. In addition, anti-acrosin antibody with low binding specificity has been used for western blotting [5]. There are several types of spectrophotometry assay, including an acrosin/proacrosin target with N-α-benzoyl-dl-arginine-p-nitroanilide (BAPNA) substrate (spectrophotometry/BAPNA) [68]; acrosin/proacrosin target with BAPNA substrate in a commercially available acrosin activity assay kit (Accu-Sperm) (Accu-Sperm spectrophotometry/BAPNA) [9]; acrosin/proacrosin target with N-benzoyl-l-arginine ethyl ester (BAEE) substrate (spectrophotometry/BAEE) [10, 11]; acrosin/proacrosin/acrosin inhibitor target with BAEE substrate [12]; and hyaluronidase target with BAEE substrate [13]. Substrate assays include a hyaluronidase target with cytochemical substrate [14]; acrosin target with gelatine substrate [1518]; hyaluronidase target with agar/hyaluronic acid mixture substrate [19]; and hyaluronidase target with hyaluronic acid substrate [2]. Finally, an RIA has been used to quantify acrosin in sperm acid extracts irrespective of the presence of acrosin inhibitors [20].
For assessing human sperm AR, three kinds of methods are used, including transmission electron microscopy (TEM), dyes for bright-field microscopy (DBM), fluorescent labels [21]. For the TEM, it is usually the god standard against which a new assay is measured and it cannot be routinely used owing to labor consuming and lack of sperm viability assay [21]. For the DBM, two stain (an acrosomal stain, a nuclear stain) [22] and triple stain (Bismark brown, rose Bengal, trypan blue) [23, 24] are the most widely used. There are three classes of fluorescent labels: those that label permeabilized spermatozoa with internally directed probes, including fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm (FITC-PSA) [2536], peanut agglutinin (FITC-PNA) [3739], Concanavalin A lectin (FITC-Con A) [40], GB24 antibody (FITC-GB24) [41, 42], rhodamine-conjugated PSA (RITC-PSA) [43], and tetramethylrhodamine-conjugated PSA (TRITC-PSA) [44]; those that label permeabilized spermatozoa with by indirect immunofluorescence with antibodies—including HS21 [45], HS63 [46], GB24 [37, 47], MH61 [29], anti-CD46 [48]—directed against acrosome-associated antigens; and those—such as chlortetracycline (CTC) [49]—that can be used on living, nonpermeabilized cells.
Conflicting results have been reported concerning the utility of acrosome function scoring determined by different methods for predicting fertilization rate (FR) in vitro. Some studies showed that there was no correlation between acrosome function scoring and FR [9, 10, 41, 50, 51]. In contrast, others have reported a positive correlation between the two parameters by fluorometry [3, 4], spectrophotometry [3, 68, 5258], and substrate assay [2, 1519]. To clarify this contradiction, we retrospectively investigated the correlation between AE levels determined by spectrophotometry/BAPNA with FR. Additionally, a systematic review and meta-analysis of published literature on similar topic, without regard to acrosome function assay methods, was performed to further expand upon the findings.

Methods

Retrospective cohort study

Patients

From July 2015 to March 2016, 737 infertile couples undergoing in vitro fertilization (IVF) therapy for whom ≥4 MII oocytes used for fertilization in vitro on the day of therapy, while excluding those presenting for IVF with intracytoplasmic sperm injection (ICSI) therapy, were included in retrospective analysis. The aetiologies of infertility were as follows: male factor in 133 (single problem = 93; oligozoospermia: 6, asthenozoospermia: 38, teratozoospermia: 49; ≥ 2 male problems mentioned above = 40); female factor in 353 (single problem = 195; tubal occlusion: 190, ovulatory disorder: 0, endometriosis: 1, polycystic ovarian syndrome: 0, intrauterine adhesion: 1, uterine myomas: 1, uterine malformation: 0, genital tract malformation: 0, pelvic inflammatory disease: 2, immune infertility: 0, adiposis: 0, hyperlipemia: 0, hyperprolactinemia: 1; ≥ 2 female problems mentioned above = 158); couple factors in 251(≥ 1 male problem and ≥ 1 female problem mentioned above).

AE determination

Prior to further inclusion of couples in therapy protocol, the semen samples were collected and AE levels were determined by the procedure of Kennedy [6], with proper modifications. Briefly, the experimental and control tubes, each containing 7.5 ×  106 spermatozoa, were layered over 500 μL of 11% Ficoll (Sigma-Aldrich, St. Louis, MO, USA) and centrifuged at 2000×g for 20 min. Then 100 μL of benzamidine (500 mM, Sigma-Aldrich, St. Louis, MO, USA) was added to equal volume of sperm pellet in the control tube. Afterwards, 1 mL of substrate-detergent mixture (BAPNA-Triton X-100 mixture, PH = 8.0, Sigma-Aldrich, St. Louis, MO, USA) was added to both tubes. After 1 h of incubation at 24 °C, benzamidine (100 μL) was added to experimental tube to stop the reaction. All samples were centrifuged at 2000×g for 15 min and the absorbance of supernatants was spectrophotometrically determined at 410 nm. AE activity (μIU/106) was calculated out of the difference in optical density between experimental and control tube of each sample.

Meta-analysis

Data sources and study selection

Two investigators independently carried out a search in PubMed, Web of Science, Cochrane Library, Embase, EBSCO, Ovid, ClinicalTrials.​gov and Google Scholar databases for relevant literature up to February 2017. The [Title/Abstract] search was restricted to English language publications and was performed for the following MeSH terms: fertilization in vitro, acrosin, acrosome reaction, exocytosis, predictive value of tests, sensitivity and specificity (Additional file 1: search strategy). Inclusion criteria were as follows: (1) prospective cohort or case-control design; (2) infertile couples undergoing IVF therapy; (3) a study population of at least 30 couples; (4) AE or AR assay as an index test; (5) oocytes examined to establish fertilization as a reference standard test.

Data extraction and quality assessment

Information on study characteristics was independently abstracted by two investigators according to a standardized table (Table 24), with decisions made by consensus in cases of disagreement. In four articles where there were ≥ 1 outcome indicators, data with a maximal correlation coefficient and corresponding 95% confidence interval (CI) were used [16, 18, 25, 44]. In four articles where there were ≥ 1 AE/AR cut-off values, data with the best sensitivity (SEN) or specificity (SPE) were used [3, 6, 39, 59]. The methodological quality of eligible articles was assessed with the QUADAS-2 tool [60]. Based on user guidelines, items were tailored by omitting or modifying some signaling questions [60]; for example, when reviewing Patient Selection, the item “Was a case–control design avoided?” was omitted; and for a review of Objective Index Test, the item “If a threshold was used, was it pre-specified?” was substituted with “Was the method of determining AEs or AR described?” This substitution was made because candidate articles were included regardless of the method of acrosome function detection.

Statistical analysis

In retrospective cohort study, the statistical analysis was performed by SPSS version 16.0 for Windows (SPSS Inc., Chicago, IL, USA). Data were presented as number and percentages for categorical variables, while non-normal variables were reported as median and interquartile ranges. Spearman rank analysis was performed to determine which variables were related to FR. The Pearson χ2-test was performed for comparison for the frequencies of categorical variables. Two-tailed p <  0.05 was considered statistically significant. In meta-analysis, data analysis was performed using STATA 12.0 software (Stata Corp., College Station, TX, USA). Statistical heterogeneity was evaluated using the Q test or inconsistency index (I2), with significance set at p <  0.05 or I2 >  50%, respectively. If heterogeneity existed, the random effects model was adopted; otherwise, a fixed-effects model was selected. SEN and subgroup analyses were carried out to identify suspected sources of heterogeneity. Subgroups were compared with the Q test for heterogeneity [61]. The bivariate mixed effects regression model of midas module in STATA 12.0 was used for calculating SEN, SPE, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic score (DS), diagnostic odds ratio (DOR), and for performing the summary receiver operating characteristic (SROC) curve analysis and drawing Fagan nomogram.

Results

Retrospective cohort study

The baseline characteristics, AE result, and fertilization rate for the couples included in the analysis are described in Table 1. The sample size retrieved (n = 737) for this retrospective study was greater than the calculated values (334–687) for cohort study by Epi Info version 7.2 for Windows (https://​www.​cdc.​gov/​epiinfo/​pc.​html), with two-sided confidence level set at 95%, power set at 90%, ratio (unexposed: exposed) set at 0.1945 (120/617), and the % outcomes in unexposed group set at 5–10% (i.e., the occurrence of total fertilization failure [TFF, FR = 0%] described previously [62]. The median and interquartile range obtained for AE levels was 13.78 μIU/106 spermatozoa (12.12 μIU/106 spermatozoa). The FR was shown to be positively correlated with forward progression motility (spearman r = 0.119, p = 0.001) and AE levels (spearman r = 0.075, p = 0.042; Additional file 2: Table S1). According to a previously published report [6], patients were separated into two groups (< 25 μIU/106 spermatozoa, ≥ 25 μIU/106 spermatozoa), based on the AE levels results. Significantly higher FR were obtained in the group with AE activity ≥25 μIU/106 spermatozoa, compared with those with AE activity < 25 μIU/106 spermatozoa (78.98% [1101/1394], n = 120 vs. 73.31% [4843/6606], n = 617, p <  0.001). The lower AE result with a cut-off value of <25μIU/106 spermatozoa was not a risk factor for patients suffering from TFF (risk ratio [RR] = 1.46, 95% CI: 0.52–4.07), and was used for predicting TFF, showing moderate SEN (88.23% [30/34]) and low SPE (16.50% [116/703], Additional file 3: Table S2).
Table 1
Baseline characteristics, AE result, and fertilization rate for the couples included in the analysis
Variables
Median (interquartile range)
N
Female age (years)
29 (5)
737
Male age (years)
34 (7)
737
MII oocytes (n)
9 (8)
737
Abstinence days (n)
4 (2)
737
Semen volume (mL)
3.20 (1.5)
737
Concentration (× 106/mL)
42.00 (36)
737
Motility (%)
50.00 (12.6)
737
Forward progression motility (%)
35.10 (9.1)
737
Percentage of normal morphology (%)
4.46 (0.94)
737
Infertility duration (years)
4 (2)
737
Infertile diagnoses, n (%)
 Male factor
133 (18.05%)
737
 Female factor
353 (47.90%)
 Couple factors
251 (34.05%)
Infertile types, n (%)
 Primary infertility
476 (64.59%)
737
 Secondary infertility
261 (35.41%)
 
Ovulation inducing protocols, n (%)
 Conventional long pituitary downregulation protocol
35 (4.75%)
737
 Modified ultra-long pituitary downregulation protocol
702 (95.25%)
 
AE levels (μIU/106 spermatozoa)
13.78 (12.12)
737
FRa (%)
74.30 (5944/8000)
737
AE acrosomal enzyme, MII metaphase II, IVF in vitro fertilization, FR fertilization rate
aTotal fertilized oocytes/total MII oocytes

Meta-analysis

Literature search results

We initially identified 16,024 candidate articles through database searches (n = 15,772) and additional records (n = 252). After removing 7606 duplicates, we browsed the titles and abstracts of 8418 articles and selected 579 for full-text reading. The reasons for excluding the others were as follows: irrelevant (n = 3043); non-human (n = 4405); case report/review (n = 224); protocol/patent: (n = 24; protocol: 21, patent: 3); meeting abstract (n = 45); and non-English (n = 97; Chinese: 75, Iranian: 1, French: 3, Japanese: 16, German: 2), and Letter (n = 1). Of the 44 selected articles, 16 articles [3, 4, 69, 16, 18, 19, 50, 51, 5357] addressed the relationship between the AE levels and FR (Table 2); one described three AE assay methods [3]; another reported three sperm preparation methods [54]; and three also mentioned different preparation methods [4, 7, 9] for a total of 23 total datasets extracted from these 16 articles, comprising 2734 infertile couples undergoing IVF therapy. A total of 13 articles [22, 29, 33, 36, 37, 3942, 44, 47, 63, 64] addressed the relationship between the spontaneous AR% and FR (Table 3); one described two AR assay methods [37] for a total of 14 total datasets extracted from these articles, comprising 791 infertile couples. A total of 23 articles [2328, 3035, 3739, 4143, 47, 48, 59, 63, 64] addressed the relationship between the induced AR% and FR (Table 4); one described two AR assay methods [37]; another reported five AR triggers [41]; and two also mentioned different triggers [39, 42] for a total of 30 total datasets extracted from these articles, comprising 1831 infertile couples (Fig. 1a).
Table 2
Characteristics of datasets that addressed the relationship between the AE levels and FR
First author and year
Country
Design
N
Preparation method
Storage method
AE assay method
FR cut-off value
AE cut-off value
Outcome
Kruger 1988 [50]
USA
Prospective cohort
60
No preparation
Cryopreservation
Spectrophotometry/BAEE
>  0% vs. = 0%
 
Kennedy 1989 [6]
USA
Prospective cohort
35
No preparation
Fresh
Spectrophotometry/BAPNA
>  0% vs. = 0%
/= 0%
<  25μIU/106 spermatozoa
②/③
Tummon 1991a [7]
USA
Prospective cohort
87
No preparation
Fresh
Accu-Sperm Spectrophotometry/BAPNA
>  0% vs. = 0%
/= 0%
<  4.5
②/③
Tummon 1991b [7]
USA
Prospective cohort
87
Swim up
Fresh
Accu-Sperm Spectrophotometry/BAPNA
>  0% vs. = 0%
 
Albert 1992a [4]
France
Prospective case-control
50
No preparation
Fresh
MAb 4D4-proacrosin
Wholea①
/>  0% vs. = 0%
/= 0%
≤ 50%
①/②/③
Albert 1992b [4]
France
Prospective case-control
50
Swim up
Fresh
MAb 4D4-proacrosin
>  0% vs. = 0%
 
Senn 1992a [3]
Switzerland
Prospective cohort
151
Discontinuous gradient
Fresh
PAb-acrosin
>  0% vs. =0%
/= 0%
<  60%
②/③
Senn 1992b [3]
Switzerland
Prospective cohort
148
Discontinuous gradient
Fresh
PAb-hyaluronidase
>  0% vs. = 0%
/= 0%
<  80%
②/③
Senn 1992c [3]
Switzerland
Prospective cohort
96
Discontinuous gradient
Fresh
Spectrophotometry/BAPNA
= 0%
<  30 μIU/106 spermatozoa
De Jonge 1993 [8]
USA
Prospective cohort
21/60
No preparation
Fresh
Spectrophotometry/BAPNA
>  70%b①
/≥ 70% vs. <  70%
<  12.8 μIU/106 spermatozoa
①/②
Sharma 1993a [54]
UK
Prospective cohort
46
Swim up
Fresh
Spectrophotometry/BAPNA
Whole
 
Sharma 1993b [54]
UK
Prospective cohort
31
Discontinuous gradient
Fresh
Spectrophotometry/BAPNA
Whole
 
Sharma 1993c [54]
UK
Prospective cohort
25
α-Chymotrypsin
Fresh
Spectrophotometry
/BAPNA
Whole
 
Bartoov 1994 [57]
Israel
Prospective case-control
59
No preparation
Fresh
Spectrophotometry
/BAPNA
Whole
/>  50% vs. = 0%/= 0%
≤ 54 μIU/106 spermatozoa
①/②/③
Sofikitis 1994 [51]
USA
Prospective cohort
41
No preparation
Fresh
Accu-Sperm
Spectrophotometry
/BAPNA
> 0% vs. = 0%
 
Yang 1994a [9]
China
Prospective cohort
95
No preparation
Fresh
Accu-Sperm
Spectrophotometry
/BAPNA
Whole
/>  0% vs. = 0%
 
①/②
Yang 1994b [9]
China
Prospective cohort
95
Swim up
Fresh
Accu-Sperm
Spectrophotometry
/BAPNA
Whole
/>  0% vs. = 0%
 
①/②
Abdul-Aziz 1995 [19]
Canada
Prospective cohort
160
No preparation
Fresh
Hyaluronidase target with agar/hyaluronic acid mixture substrate
Whole
≤ 3 mm
Henkel 1995
[16]
Germany
Prospective cohort
110
Swim up
Fresh
Acrosin target with gelation substrate assay
whole/
≤ 50%
<  6
①/③
Menkveld 1996 [55]
Netherlands
Prospective cohort
33
No preparation
Fresh
Spectrophotometry
/BAPNA
whole
/≥ 50% vs. <  50%/<  50%
≤ 18 μIU/106 spermatozoa
①/②/③
Yie 1996
[53]
Canada
Prospective cohort
259
Swim up
Cryopreservation
Spectrophotometry
/BAPNA
> 0% vs. 0%
/= 0%
≤ 15 μIU/
μgDNA
②/③
Langlois 2005
[56]
Belgium
Prospective cohort
107
No preparation
Fresh
Spectrophotometry
/BAPNA
whole
/≥ 50% vs. <  50%/<  50%
<  25 μIU/106 spermatozoa
①/②/③
Tavalaee 2007 [18]
Iran
Prospective cohort
48
Discontinuous gradient
Fresh
Acrosin target with gelation substrate assay
whole
/<  50%
<  60%
①/③
AE acrosomal enzyme, FR fertilization rate, BAEE N-benzoyl-l-arginine ethyl ester, BAPNA N-α-benzoyl-dl-arginine-p-nitroanilide
aAll infertile patients undergoing in vitro fertilization (IVF) therapy
bInfertile patients for whom ≥70% fertilization was achieved by IVF
①spearman correlation coefficient; ② AE levels for higher and lower FR; ③ binary diagnostic accuracy data as 2 × 2 tables
Table 3
Characteristics of datasets that addressed the relationship between the spontaneous AR% and FR
First author and year
Country
Design
N
Preparation method
Assay method
FR cut-off value
AR cut-off value
Outcome
Fénichel 1991 [47]
France
Prospective cohort
41
Swim up
GB24
>  0% vs. = 0%
 
Takahashi 1993 [40]
Japan
Prospective cohort
45
Discontinuous gradient
FITC-Con A
<  50%
%AR ≥ 10% at 2 h or ≤ 5% at 4 h
Parinaud 1993a [37]
France
Prospective cohort
53
Discontinuous gradient
FITC-PNA
>  0% vs. = 0%
 
Parinaud 1993b [37]
France
Prospective cohort
53
Discontinuous gradient
GB24
>  0% vs. = 0%
 
Parinaud 1995 [41]
Monaco
Prospective cohort
117
Discontinuous gradient
F1TC-GB24
Wholea
 
Parinaud 1995 [42]
Monaco
Prospective cohort
131
Discontinuous gradient
FITC-GB24
>  0% vs. = 0%
 
Krausz 1996
[39]
Italy
Prospective cohort
59
Swim up
FITC-PNA
≥ 50% vs. <  50%
 
Hershlag 1997
[44]
USA
Prospective cohort
74
Swim up
TRITC-PSA
Whole
 
Fujino 1997
[22]
Japan
Prospective cohort
30
Discontinuous gradient + Swim up
Two stain (new-methylene blue and cresyl violet) Blutstan kit
Whole
 
Rufas 1998
[64]
Israel
Prospective cohort
62
Discontinuous gradient
FITC-PSA
>  0% vs. = 0%
 
Kawamoto 1999
[29]
Japan
Prospective cohort
34
Swim up
MH61
>  0% vs. = 0%
 
Bastiaan 2003
[63]
South Africa
Prospective cohort
30
Swim up
FITC-PSA
>  50% vs. <  50%
 
El-Ghobashy 2003
[33]
UK
Prospective cohort
75
Swim up
FITC-PSA
≥ 50% vs. <  50%
 
Wiser 2014
[36]
Israel
Prospective cohort
40
Not reported
FITC-PSA
≤ 35%
≤10%
AR acrosome reaction, FR fertilization rate, FITC-ConA fluorescein isothiocyanate-conjugated Concanavalin A lectin, FITC-PNA fluorescein isothiocyanate-conjugated peanut agglutinin, FITC-GB24 fluorescein isothiocyanate-GB24, TRITC-PSA tetramethylrhodamine-conjugated Pisurn sativum agglutimm, FITC-PSA fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm
aAll infertile patients undergoing in vitro fertilization (IVF) therapy
① spearman correlation coefficient; ② spontaneous AR% for higher and lower FR; ③ binary diagnostic accuracy data as 2 × 2 tables
Table 4
Characteristics of datasets that addressed the relationship between the induced AR% and FR
First author and year
Country
Design
N
Preparation method
Inducer
Assay method
FR cut-off value
AR cut-off value
Outcome
Fénichel 1991
[47]
France
Prospective cohort
41
Swim up
A23187
GB24
>  0% vs. = 0%
/= 0%
Spontaneous AR% ≥ 11.6% and/or Induced AR% < 20.6%
②/③
Pampiglione 1993
[23]
UK
Prospective cohort
54
Swim up
A23187
Triple stain
>  0% vs. = 0%
/= 0%
<  31.3%
②/③
Parinaud 1993a
[37]
France
Prospective cohort
53
Discontinuous gradient
A23187
FITC-PNA
>  0% vs. = 0%
 
Parinaud 1993b
[37]
France
Prospective cohort
53
Discontinuous gradient
A23187
GB24
>  0% vs. = 0%
 
Henkel 1993
[59]
Germany
Prospective cohort
74
Swim up
Low temperature
Triple stain
<  50%
≤ 10%
Calvo 1994
[25]
USA
Prospective cohort
82
/232
No preparation
HFF
FITC-PSA
Wholea①/= 0%
≤ 5%
①/③
Yovich 1994
[26]
Australia
Prospective cohort
52
Swim up
/Discontinuous gradient
A23187
FITC-PSA
= 0%
<  10%
Parinaud 1995a
[41]
Monaco
Prospective cohort
117
Discontinuous gradient
A23187
FITC-GB24
Whole
/>  0% vs. = 0%
 
①/②
Parinaud 1995b
[41]
Monaco
Prospective cohort
117
Discontinuous gradient
P
FITC-GB24
Whole
/>  0% vs. = 0%
 
①/②
Parinaud 1995c
[41]
Monaco
Prospective cohort
117
Discontinuous gradient
HFF
FITC-GB24
Whole
/>  0% vs. = 0%
 
①/②
Parinaud 1995d
[41]
Monaco
Prospective cohort
117
Discontinuous gradient
CAMP
FITC-GB24
Whole
/>  0% vs. = 0%
 
①/②
Parinaud 1995e
[41]
Monaco
Prospective cohort
117
Discontinuous gradient
TPA
FITC-GB24
Whole
/>  0% vs. = 0%
 
①/②
Sukcharoen 1995
[38]
UK
Prospective cohort
41
Discontinuous gradient
A23187
FITC-PNA
>  0% vs. <  50%
 
Parinaud 1995a
[42]
Monaco
Prospective cohort
131
Discontinuous gradient
A23187
FITC-GB24
>  0% vs. = 0%
 
Parinaud 1995b
[42]
Monaco
Prospective cohort
131
Discontinuous gradient
TPA
FITC-GB24
>  0% vs. = 0%
 
Brandelli 1995
[27]
Argentina
Prospective cohort
31
Discontinuous gradient
BSA-GlcNAc/A23187
FITC-PSA
Whole
/≥ 30% vs. <  30%
/<  30%
<  0.2b③
①/②/③
Krausz 1996a
[39]
Italy
Prospective cohort
53/51
/52
Swim up
A23187
FITC-PNA
Whole
/≥ 50% vs. <  50%
/= 0%
≤ 10%
①/②/③
Krausz 1996b
[39]
Italy
Prospective cohort
59
/59
/60
Swim up
P
FITC-PNA
Whole
/≥ 50% vs. <  50%
/= 0%
≤ 7%
①/②/③
Carver-Ward 1996
[48]
Netherlands
Prospective cohort
129
Discontinuous gradient
A23187
Anti-CD46
antibody
Whole
/≤ 30%
≤ 10%
①/③
Benoff 1997
[43]
USA
Prospective cohort
58
Swim up
Mannose
RITC-PSA
Whole
/≥ 63% vs. <  63%
/<  63%
≤ 0.1c③
①/②/③
Liu 1998
[28]
Australia
Prospective cohort
109
Discontinuous gradient
A23187
FITC-PSA
Whole
/>  50% vs. ≤ 50%
 
①/②
Rufas 1998
[64]
Israel
Prospective case-control
62
Discontinuous gradient
HFF
FITC-PSA
>  0% vs. = 0%
 
Fukui 2000
[30]
Japan
Prospective cohort
39
Discontinuous gradient
P
FITC-PSA
>  0% vs. = 0%
 
Esterhuizen 2001
[31]
South Africa
Prospective cohort
35
Swim up
ZP
FITC-PSA
Whole
/≤ 60%
≤ 15%
①/③
Bastiaan 2003
[63]
South Africa
Prospective cohort
30
Swim up
ZP
FITC-PSA
>  50% vs. <  50%
/≤ 50%
<  8%
②/③
Liu 2003
[32]
Australia
Prospective cohort
65
Swim up
ZP
FITC-PSA
Whole
/<  30%
≤ 16%
①/③
El-Ghobashy 2003 [33]
UK
Prospective cohort
75
Swim up
HFF
FITC-PSA
Whole
/≥ 50% vs. <  50%
 
①/②
Katsuki 2005
[34]
Japan
Prospective cohort
133
Swim up
A23187
FITC-PSA
>  0% vs. = 0%
/= 0%
<  21%
②/③
Jędrzejczak 2005
[24]
Poland
Prospective cohort
79
Discontinuous gradient
A23187
Triple stain
Whole
 
Abu 2012
[35]
South Africa
Prospective cohort
78
Double Swim up
ZP
FITC-PSA
Whole
 
AR acrosome reaction, FR fertilization rate, HFF human follicle fluid, P progesterone, ZP zona pellucida, CAMP cyclic adenosine 3′-5′-phosphate analogue, TPA phorbol ester, BSA-GlcNAc Neoglycoproteins with N-acetylglucosamine residues, FITC-PNA fluorescein isothiocyanate-conjugated peanut agglutinin, FITC-PSA fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm, FITC-GB24 fluorescein isothiocyanate-GB24, RITC-PSA rhodamine-conjugated Pisurn sativum agglutimm
aAll infertile patients undergoing in vitro fertilization (IVF) therapy
bBSA-GlcNAc induced increased %AR/A23187 induced increased %AR
cMannose induced increased %AR/Mannose induced total %AR
① spearman correlation coefficient; ② induced AR% for higher and lower FR; ③ binary diagnostic accuracy data as 2 × 2 tables

Study characteristics

All included 44 articles comprised at least four items of low bias in QUADAS 2, indicating high overall quality (Fig. 1b). Forty-one had a prospective cohort design and three had a prospective case-control design. Geographic areas included Asia (n = 10), North America (n = 10), Europe (n = 17), Africa (n = 3), Oceania (n = 2), and South America (n = 2). Sperm storage methods included fresh samples (n = 41, for AE assay: 13, for AR assay: 28) and cryopreservation (n = 3; for AE assay: 3, for AR assay: 0). Sperm preparation methods included no preparation (n = 12), one preparation (n = 34; α-chymotrypsin: 1; swim up: 18; discontinuous gradient: 14; swim up/discontinuous gradient: 1;), double preparation (n = 2; swim up after discontinuous gradient: 1; double swim up: 1), and not reported (n = 1). AE assay methods included fluorometry (n = 3; pAb-acrosin: 1, pAb-hyaluronidase: 1, mAb 4D4-proacrosin: 1), spectrophotometry (n = 13; spectrophotometry/BAPNA: 9, Accu-Sperm spectrophotometry/BAPNA: 3, spectrophotometry/BAEE: 1), and substrate assay (n = 3; acrosin target with gelatine substrate assay: 2, hyaluronidase target with agar/hyaluronic acid mixture substrate assay: 1). All spectrophotometry in the 16 articles had acrosin/proacrosin as targets. AR triggers included physiological triggers (n = 10; human follicle fluid [HFF]: 4, progesterone [P]: 3, zona pellucida [ZP]: 3,) and nonphysiological triggers (n = 18; calcium ionophore A23187: 12, low temperature: 1, cyclic adenosine 3′-5′-phosphate analogue [CAMP]: 1, phorbol ester [TPA]: 2, Neoglycoproteins with N-acetylglucosamine residues [BSA-GlcNAc]: 1, mannose: 1). AR assay methods included DBM (n = 4, two stain Blutstan kit: 1, triple stain: 3) and fluorescent labels (n = 24; direct immunofluorescence with lectin: FITC-PSA: 12, FITC-PNA: 3, FITC-ConA: 1, RITC-PSA: 1, TRITC-PSA:1; direct immunofluorescence with antibody: FITC-GB24: 3; indirect immunofluorescence: GB24 antibody: 1, anti-CD46 antibody: 1, MH61 antibody: 1).

Data synthesis and analysis

Engauge Digitizer software (http://​markummitchell.​github.​io/​engauge-digitizer/​) was used to convert the scatter plots in seven articles [6, 7, 18, 27, 38, 39, 63] into coordinates to indirectly obtain acrosome function scoring and FRs. Pearson correlation coefficient from thirteen studies [4, 8, 9, 18, 22, 24, 31, 39, 41, 43, 44, 54, 55] was converted into spearman correlation coefficient (Rs) values followed by Fisher’s r-to-z and z-to-r transformation.

AE assay

Rs was extracted from 10 articles that included a total of 758 infertile couples. A total of 13 datasets were analyzed, including one article each that used three [54] and two [9] sperm preparation methods. AE levels and FRs that were higher and lower than the respective cut-off values were extracted from 12 articles, which included a total of 1037 infertile couples. Of the 16 datasets analyzed, one used two AE assay methods [3] and three used two sperm preparation methods [4, 7, 9]. Binary accuracy data from 939 infertile couples were extracted from 10 articles as 2 × 2 tables. We analyzed the 12 datasets, including one paper that used three assay methods [3] (Table 2).
According to a random-effects model, AE levels were positively correlated with FR (Rs = 0.39, 95% CI: 0.18–0.60, p <  0.001), albeit with notable heterogeneity (I2 = 95.7%, p <  0.001; Table 3; Fig. 2a, Table 5). Higher AE levels were obtained for higher as compared to lower FRs (standardized mean difference [SMD] = 0.79, 95% CI: 0.53–1.05, p <  0.001; Fig. 2b, Table 6). The bivariate mixed effects regression model predicted lower FR for lower AE levels with pooled low SEN/moderate SPE (SEN = 0.57, 95% CI: 0.41–0.71; SPE = 0.85, 95% CI: 0.73–0.93), moderate discriminant effect (PLR = 3.91, 95% CI: 2.31–6.61; NLR = 0.50, 95% CI: 0.37–0.68; DS = 2.05, 95% CI: 1.43–2.67; DOR = 7.78, 95% CI: 4.19–14.46) and moderate accuracy (area under the SROC curve [AUC] = 0.78, 95% CI: 0.74–0.81; Fig. 2ce, Table 7). The Fagan nomogram showed that lower AE levels could be used to predict lower FR when the pre-test probability was 27% (i.e., occurrence rate of patients for whom < 70% fertilization was achieved by IVF in our hospital), with a post-test probability of 59%.
Table 5
Summary of Rs values for AE assay
Subgroup
N
Rs (95% CI)
Test(s) of heterogeneity
Significance test(s) of Rs = 0
P a
I2 (%)
P
Z
P
 
Overall
13
0.39 (0.18–0.60)
95.7
0.000
3.70
0.000
 
Two experiments excluded
11
0.38 (0.27–0.48)
67.1
0.001
7.19
0.000
 
Geographic area
 Asia
4
0.24 (0.05–0.42)
66.7
0.029
2.49
0.013
< 0.001
 North America
1
0.54 (0.43–0.65)
b
9.70
0.000
 
 Europe
6
0.46 (0.37–0.54)
0.0
0.798
11.02
0.000
 
Preparation method
 No preparation
6
0.42 (0.30–0.55)
63.4
0.018
6.72
0.000
0.04
 Swim up
3
0.27 (0.01–0.53)
80.6
0.006
2.01
0.044
 
 Discontinuous gradient
2
0.42 (0.23–0.60)
0.0
0.893
4.41
0.000
 
AE assay method
 Fluorometry
  MAb 4D4-proacrosin
1
0.49 (0.27–0.70)
4.43
0.000
< 0.001
 Spectrophotometry
  Spectrophotometry/BAPNA
5
0.44 (0.35–0.54)
0.0
0.618
9.08
0.000
 
  Accu-Sperm spectrophotometry/BAPNA
2
0.09 (−0.05–0.23)
0.0
0.352
1.22
0.223
 
 Substrate assay
  Acrosin target with gelatine substrate assay
2
0.43 (0.30–0.56)
0.0
0.997
6.51
0.000
 
  Hyaluronidase target with agar/hyaluronic acid mixture substrate assay
1
0.54 (0.43–0.65)
9.70
0.000
 
Rs spearman correlation coefficient, CI confidence interval, BAPNA N-α-benzoyl-dl-arginine-p-nitroanilide
aComparison between subgroups with the Q test for heterogeneity
bNot calculated
Table 6
Summary of SMD values for AE assay
Subgroup
N
SMD (95% CI)
Test(s) of heterogeneity
Significance test(s) of SMD = 0
P a
I2 (%)
P
Z
P
 
Overall
16
0.79 (0.53–1.05)
74.5
0.000
5.97
0.000
 
Four experiments excluded
12
0.75 (0.57–0.93)
26.5
0.184
8.19
0.000
 
Geographic areas
       
 Asia
3
0.50 (0.15–0.85)
2.3
0.359
2.77
0.006
0.026
 North America
7
0.81 (0.39–1.22)
74.2
0.001
3.80
0.000
 Europe
6
0.92 (0.48–1.36)
80.8
0.000
4.08
0.000
Storage method
       
 Cryopreservation
2
0.20 (−0.11–0.52)
0.0
0.425
1.27
0.204
< 0.001
 Fresh
14
0.89 (0.63–1.15)
69.3
0.000
6.73
0.000
Preparation method
       
 No preparation
10
0.82 (0.50–1.13)
63.1
0.004
5.14
0.000
0.023
 Swim up
4
0.57 (0.20–0.94)
53.6
0.091
3.04
0.002
 Discontinuous gradient
2
1.07 (−0.10–2.25)
95.1
0.000
1.79
0.074
FR cut-off value combined with AE assay method
≥ 70% vs. <  70%
Spectrophotometry
      
NC
 
Spectrophotometry/BAPNA
1
0.86 (0.30–1.41)
b
3.03
0.002
 
≥ 50% vs. <  50%
Spectrophotometry
 
Spectrophotometry/BAPNA
2
0.94 (0.18–1.71)
72.5
0.056
2.41
0.016
 
>  50% vs. = 0%
Spectrophotometry
 
Spectrophotometry/BAPNA
1
0.82 (0.26–1.38)
2.87
0.004
 
>  0% vs. = 0%
Fluorometry
 
PAb-acrosin
1
1.68 (1.29–2.07)
  
8.45
0.000
 
 
PAb-hyaluronidase
1
0.48 (0.13–0.82)
  
2.68
0.007
 
 
MAb 4D4-proacrosin
2
0.72 (0.32–1.13)
0.0
0.600
3.50
0.000
 
 
Spectrophotometry
       
 
Spectrophotometry/BAPNA
2
1.23 (−0.74–3.19)
93.5
0.000
1.22
0.221
 
Accu-Sperm spectrophotometry/BAPNA
5
0.70 (0.41–0.99)
22.5
0.271
4.70
0.000
 
Spectrophotometry/BAEE
1
−0.04 (−0.72–0.64)
0.12
0.908
 
SMD standardized mean difference, CI confidence interval, BAPNA N-α-benzoyl-dl-arginine-p-nitroanilide, BAEE N-benzoyl-l-arginine ethyl ester, NC not compared
aComparison between subgroups with the Q test for heterogeneity
bNot calculated
Table 7
Summary of SEN, SPE, PLR, NLR, DS, DOR, and AUC values for AE assay
Subgroup
N
SEN (95% CI)
SPE (95% CI)
PLR (95% CI)
NLR (95% CI)
DS (95% CI)
DOR (95% CI)
AUC (95% CI)
P a
Overall
12
0.57 (0.41–0.71)
0.85 (0.73–0.93)
3.91
(2.31–6.61)
0.50
(0.37–0.68)
2.05 (1.43–2.67)
7.78 (4.19–14.46)
0.78 (0.74–0.81)
 
Outlier excluded
11
0.51 (0.39–0.62)
0.88 (0.79–0.94)
4.22
(2.42–7.36)
0.56
(0.45–0.69)
2.02 (1.37–2.67)
7.53 (3.92–14.47)
0.73 (0.69–0.77)
 
Storage method
 Cryopreservation
1
0.51
0.51
1.06
0.95
c
1.12
< 0.001
 Fresh
11
0.60 (0.41–0.76)
0.87 (0.77–0.93)
4.64 (3.04–7.08)
0.46 (0.32–0.68)
2.30 (1.80–2.80)
9.99 (6.05–16.49)
0.83 (0.80–0.86)
 
Preparation method
 No preparation
6
0.72 (0.50–0.87)
0.80 (0.59–0.92)
3.68 (1.90–7.13)
0.35 (0.21–0.59)
2.36 (1.71–3.01)
10.56 (5.51–20.26)
0.83 (0.79–0.86)
0.006
 Swim up
4b
0.38 (0.24–0.54)
0.86 (0.49–0.97)
2.63 (0.75–9.18)
0.73 (0.62–0.85)
1.29 (− 0.06–2.63)
3.62 (0.94–13.90)
0.51 (0.47–0.56)
 
 Discontinuous gradient
4
0.46 (0.28–0.65)
0.90 (0.87–0.93)
4.83 (2.64–8.83)
0.60 (0.41–0.87)
2.09 (1.14–3.04)
8.08 (3.13–20.88)
0.90 (0.87–0.92)
 
FR cut-off value combined with AE assay method
<  50%
Spectrophotometry
        
NC
Spectrophotometry/BAPNA
4b
0.63 (0.48–0.76)
0.87 (0.60–0.97)
4.96 (1.51–16.37)
0.42 (0.32–0.57)
2.46 (1.24–3.67)
11.68 (3.47–39.36)
0.75 (0.71–0.79)
 
Substrate assay
Acrosin target with gelatine substrate assay
1
0.50
0.93
7.00
0.54
13.00
0.80d
 
≤ 50%
Substrate assay
Acrosin target with gelatine substrate assay
1
0.26
0.97
9.64
0.76
12.63
 
= 0%
Fluorometry
PAb-acrosin
1
0.63
0.92
9.23
0.39
23.87
 
PAb-hyaluronidase
1
0.23
0.90
2.29
0.86
2.68
 
MAb 4D4-proacrosin
1
0.40
0.96
10.00
0.63
16.00
0.71d
 
Spectrophotometry
Spectrophotometry/BAPNA
4
0.78 (0.38–0.95)
0.63 (0.40–0.81)
2.11 (1.25–3.55)
0.35 (0.11–1.18)
1.78 (0.29–3.27)
5.94 (1.34–26.34)
0.74 (0.70–0.78)
 
Accu-sperm
Spectrophotometry/BAPNA
1
0.61
0.84
3.90
0.46
8.4
 
SEN sensitivity, SPE specificity, PLR positive likelihood ratio, NLR negative likelihood ratio, DS diagnostic score, DOR diagnostic odds ratio, AUC area under the summary receiver operating characteristic curve, CI confidence interval, NC not compared
aComparison between subgroups with the Q test for heterogeneity
bConverted number = actual number × 2. Studies were duplicated for numbers ≥ 2 and < 4, based on the computation of bivariate mixed effects regression model for the lowest threshold of 4 studies
cNot calculated in original data or not reported
dCoordinates in scatter plots were converted with the Engauge digitizer to calculate AUC
After SEN analysis, two studies [8, 54] were identified as a source of heterogeneity when pooling Rs; however, after they were excluded, the correlation was unchanged (Rs = 0.38, 95% CI: 0.27–0.48, p <  0.001) and the heterogeneity while decreased was still significant (I2 = 67.1%, p = 0.001; Table 3). When SMD was pooled, four studies [3, 6, 50, 53] were found to contribute to this heterogeneity; when these were excluded, the correlation was unchanged (SMD = 0.75, 95% CI: 0.57–0.93, p <  0.001) but there was no obvious heterogeneity (I2 = 26.5%, p = 0.184; Table 4). When pooling diagnostic accuracy data, excluding one outlier [57] did not significantly change the overall results (SEN = 0.51, 95% CI: 0.39–0.62; SPE = 0.88, 95% CI: 0.79–0.94; PLR = 4.22, 95% CI: 2.42–7.36, NLR = 0.56, 95% CI: 0.45–0.69; DS = 2.02, 95% CI: 1.37–2.67; DOR = 7.53, 95% CI: 3.92–14.47; AUC = 0.73, 95% CI: 0.69–0.77; Table 7). Graphs of SROC curves generated before and after removing the outlier (Fig. 2e, f) indicated that the threshold effect applied to inter-study heterogeneity, since the spearman correlation coefficient between SEN and 1 − SPE was 0.685 (p = 0.014).
In the subgroup analysis (Table 57), datasets were stratified according to geographic area, sperm storage method, sperm preparation method, and FR cut-off value combined with AE assay method. The diagnostic performance in Asia (Rs = 0.24, 95% CI: 0.05–0.42, p = 0.013; SMD = 0.50, 95% CI: 0.15–0.85, p = 0.006) was inferior to that in North America (Rs = 0.54, 95% CI: 0.43–0.65, p <  0.001; SMD = 0.81, 95% CI: 0.39–1.22, p <  0.001) and Europe (Rs = 0.46, 95% CI: 0.37–0.54, p <  0.001; SMD = 0.92, 95% CI: 0.48–1.36, p <  0.001; comparison between subgroups [p] <  0.05). Cryopreserved spermatozoa (SMD = 0.20, 95% CI: − 0.11–0.52, p = 0.204; SEN = 0.51; SPE = 0.51; DOR = 1.12) were inferior to fresh spermatozoa (SMD = 0.89, 95% CI: 0.63–1.15, p <  0.001; SEN = 0.60, 95% CI: 0.41–0.76; SPE = 0.87, 95% CI: 0.77–0.93; DOR = 9.99, 95% CI: 6.05–16.49; comparison between subgroups [p] <  0.001). Sperm preparation yielded inferior results as compared to no preparation (Rs = 0.42, 95% CI: 0.30–0.55, p <  0.001; SMD = 0.82, 95% CI: 0.50–1.13, p <  0.001; SEN = 0.72, 95% CI: 0.50–0.87; SPE = 0.80, 95% CI: 0.59–0.92; DOR = 10.56, 95% CI: 5.51–20.26; comparison between subgroups [p] <  0.05); spermatozoa after swim up were scarcely irrelevant (Rs = 0.27, 95% CI: 0.01–0.53, p = 0.044); and there was no correlation for spermatozoa after a discontinuous gradient (SMD = 1.07, 95% CI: − 0.10–2.25, p = 0.074).
AE levels determined by fluorometry—including pAb-acrosin (SMD = 1.68, 95% CI: 1.29–2.07, p <  0.001), pAb-hyaluronidase (SMD = 0.48, 95% CI: 0.13–0.82, p = 0.007), and mAb 4D4-proacrosin (Rs = 0.49, 95% CI: 0.27–0.70, p <  0.001; SMD = 0.72, 95% CI: 0.32–1.13, p <  0.001)—were positively correlated with FR. For predicting TFF, the pAb-acrosin assay with a cut-off value of < 60% for normal fluorescence scores (SEN = 0.63, SPE = 0.92, DOR = 23.87); pAb-hyaluronidase assay with a cut-off value of < 80% for normal fluorescence scores (SEN = 0.23, SPE = 0.90, DOR = 2.68); and mAb 4D4-proacrosin assay with a cut-off value of ≤50% for the normal acrosomal principal region (SEN = 0.40, SPE = 0.96, DOR = 16.00) and low SEN and high SPE were adopted.
AE levels determined by spectrophotometry—including spectrophotometry/BAPNA (Rs = 0.44, 95% CI: 0.35–0.54, p <  0.001), Accu-Sperm spectrophotometry/BAPNA (SMD = 0.70, 95% CI: 0.41–0.99, p <  0.001)—were positively correlated with FR, but this did not apply to spectrophotometry/BAEE (SMD = − 0.04, 95% CI: − 0.72–0.64, p = 0.908). The spectrophotometry/BAPNA assay predicted an FR <  50%, with pooled low SEN (0.63, 95% CI: 0.48–0.76) and moderate SPE (0.87, 95% CI: 0.60–0.97) and DOR = 11.68 (95% CI: 3.47–39.36). Specifically, low SEN and high SPE and moderate SEN and low SPE were associated with cut-off values of 25 μIU/106 spermatozoa (SEN = 0.51, SPE = 0.97, DOR = 33.78) [58] and 18 μIU/106 spermatozoa (SEN = 0.76, SPE = 0.63, DOR = 5.42) [55]. For predicting TFF, the spectrophotometry/BAPNA assay was adopted with pooled moderate SEN and low SPE (SEN = 0.78, 95% CI: 0.38–0.95; SPE = 0.63, 95% CI: 0.40–0.81; DOR = 5.94, 95% CI: 1.34–26.34). Specifically, moderate SEN and SPE, high SEN and low SPE, low SEN and moderate SPE, and low SEN and SPE were obtained for cut-off values of 25 μIU/106 spermatozoa (SEN = 0.78, SPE = 0.73, DOR = 9.50) [6], 54μIU/106 spermatozoa (SEN = 1.00, SPE = 0.36, DOR = 23.31) [57], and 30 μIU/106 spermatozoa (SEN = 0.53, SPE = 0.86, DOR = 7.27) [3], and 15 μIU/μg DNA (SEN = 0.51, SPE = 0.51, DOR = 1.12) [53]. The Accu-Sperm spectrophotometry/BAPNA assay with a cut-off value of < 4.5 for the acrosin activity index was adopted with low SEN and moderate SPE (SEN = 0.61, SPE = 0.84, DOR = 8.40).
AE levels determined by substrate assays—including acrosin target with gelatine substrate assay (Rs = 0.43, 95% CI: 0.30–0.56, p <  0.001), and hyaluronidase target with agar/hyaluronic acid mixture substrate assay (Rs = 0.54, 95% CI: 0.43–0.65, p <  0.001) —were positively correlated with FR. For predicting an FR of ≤50% or <  50%, the acrosin target with gelatine substrate assay with a cut-off value of < 6 for acrosin activity index or <  60% for halo formation rate showed low SEN and high SPE (SEN = 0.26, SPE = 0.97, DOR = 12.63; SEN = 0.50, SPE =0.93, DOR = 13.00, respectively).
The included studies were distributed symmetrically without obvious publication bias (Deeks’ funnel plot [p] = 0.53, Fig. 4b).

Spontaneous AR assay

Rs was extracted from 3 articles that included a total of 181 infertile couples. The spontaneous AR% and FRs that were higher and lower than the respective cut-off values were extracted from 9 articles, which included a total of 602 infertile couples. Of the 10 datasets analyzed, one used two AR assay methods [37]. Binary accuracy data were extracted from only 3 articles as 2 × 2 tables; the diagnostic summary measures were not pooled, based on the computation of bivariate mixed effects regression model for the lowest threshold of 4 studies (Table 3).
According to a random-effects model, spontaneous AR% was weakly correlated with FR (Rs = 0.32, 95% CI: 0.01–0.63, p = 0.045; Fig. 3a), with notable heterogeneity (I2 = 85.1%, p = 0.001). However, the higher spontaneous AR% was not obtained for higher as compared to lower FRs when pooling SMD (SMD = − 0.30, 95% CI: –0.80–0.20, p = 0.245; Fig. 3b), with notable heterogeneity (I2 = 87.0%, p < 0.001). After SEN analysis, three studies [29, 33, 63] were identified as a source of heterogeneity; after they were excluded, the irrelevance was unchanged (SMD = − 0.06, 95% CI: –0.33–0.22, p <  0.001) but the heterogeneity significantly decreased (I2 = 46.2%, p = 0.084). The included studies were distributed symmetrically without obvious publication bias (Egger’s test [p] = 0.713, Fig. 4d).

Induced AR assay

Rs was extracted from 12 articles that included a total of 917 infertile couples. A total of 17 datasets were analyzed, including one article each that used five [41] and two [39] AR triggers. Induced AR% and FRs that were higher and lower than the respective cut-off values were extracted from 15 articles, which included a total of 1033 infertile couples. Of the 22 datasets analyzed, one used two AR assay methods [37], another reported five AR triggers [41], and two also mentioned different triggers [39, 42]. Binary accuracy data from 953 infertile couples were extracted from 12 articles as 2 × 2 tables. We analyzed the 13 datasets, including one paper that used two triggers [39] (Table 4).
According to a random-effects model, induced AR% were positively correlated with FR (Rs = 0.40, 95% CI: 0.24–0.57, p <  0.001; Fig. 3c, Table 8), albeit with notable heterogeneity (I2 = 96.5%, p <  0.001). Higher induced AR% was obtained for higher as compared to lower FRs (SMD = 0.86, 95% CI: 0.60–1.11, p <  0.001; Fig. 3d, Table 9). The bivariate mixed effects regression model predicted lower FR for lower induced AR% with pooled moderate SEN/SPE (SEN = 0.79, 95% CI: 0.71–0.85; SPE = 0.87, 95% CI: 0.74–0.94; Fig. 3e, Table 10), discriminant effect (PLR = 6.08, 95% CI: 2.77–13.36; NLR = 0.24, 95% CI: 0.17–0.35; DS = 3.22, 95% CI: 2.19–4.24; DOR = 24.91, 95% CI: 8.91–69.66; Fig. 3f, Table 10), and accuracy (AUC = 0.84, 95% CI: 0.81–0.87, Fig. 4a, Table 10). The Fagan nomogram showed that lower AE levels could be used to predict lower FR when the pre-test probability was 27%, with a post-test probability of 69%.
Table 8
Summary of Rs values for induced AR assay
Subgroup
N
Rs (95% CI)
Test(s) of heterogeneity
Significance test(s) of Rs = 0
P a
I2 (%)
P
Z
P
 
Overall
17
0.40 (0.24–0.57)
96.5
0.000
4.87
0.000
 
Three experiments excluded
14
0.36 (0.24–0.47)
83.6
0.000
5.99
0.000
 
Geographic area
 Europe
10
0.33 (0.11–0.55)
95.7
0.000
2.98
0.003
< 0.001
 Oceania
2
0.40 (0.03–0.76)
89.0
0.003
2.11
0.035
 
 South America
1
0.46 (0.17–0.75)
b
3.14
0.002
 
 Africa
2
0.65 (0.05–1.25)
97.1
0.000
2.12
0.034
 
 North America
2
0.49 (0.30–0.69)
57.8
0.124
4.95
0.000
 
Preparation method
 No preparation
1
0.39 (0.20–0.58)
4.12
0.000
< 0.001
 One preparation
15
0.41 (0.24–0.58)
96.7
0.000
4.63
0.000
 
  Swim up
6
0.65 (0.49–0.81)
93.0
0.000
8.07
0.000
< 0.001
  Swim up/discontinuous gradient
2
0.61 (0.42–0.81)
50.9
0.153
6.07
0.000
 
  Discontinuous gradient
7
0.17 (0.10–0.25)
19.0
0.285
4.42
0.000
 
 Double preparation
1
0.33 (0.13–0.53)
3.28
0.001
 
AR trigger
       
 Physiological trigger
8
0.49 (0.28–0.70)
96.8
0.000
4.51
0.000
< 0.001
  HFF
3
0.46 (−0.03–0.95)
97.3
0.000
1.85
0.065
< 0.001
  P
2
0.31(−0.01–0.63)
82.4
0.017
1.89
0.059
 
  ZP
3
0.63 (0.25–1.01)
96.0
0.000
3.22
0.001
 
 Nonphysiological trigger
9
0.33 (0.15–0.50)
89.0
0.000
3.68
0.000
 
  A23187
5
0.36 (0.13–0.58)
89.1
0.000
3.12
0.002
< 0.001
  CAMP
1
0.12(−0.06–0.29)
1.26
0.206
 
  TPA
1
0.03 (−0.15–0.21)
0.29
0.773
 
  BSA-GlcNAc/A23187
1
0.46 (0.17–0.75)
3.14
0.002
 
  Mannose
1
0.59 (0.42–0.76)
6.68
0.000
 
AR assay method
       
 Fluorescent labels
16
0.41 (0.25–0.58)
96.5
0.000
4.89
0.000
< 0.001
  Direct immunofluorescence
15
0.40 (0.21–0.58)
96.7
0.000
4.22
0.000
0.224
   With lection
10
0.53 (0.36–0.70)
94.9
0.000
6.08
0.000
< 0.001
    FITC-PSA
7
0.55 (0.36–0.75)
95.7
0.000
5.57
0.000
< 0.001
    FITC-PNA
2
0.40 (0.23–0.58)
18.3
0.269
4.51
0.000
 
    RITC-PSA
1
0.59 (0.42–0.76)
6.68
0.000
 
   With antibody
    FITC-GB24
5
0.15 (0.05–0.25)
40.3
0.152
2.93
0.003
 
  Indirect immunofluorescence
   Anti-CD46 antibody
1
0.68 (0.59–0.77)
14.14
0.000
 
 Triple stain
1
0.24 (0.03–0.45)
2.24
0.025
 
Rs spearman correlation coefficient, AR acrosome reaction, CI confidence interval, HFF human follicle fluid, P progesterone, ZP zona pellucida, CAMP cyclic adenosine 3′-5′-phosphate analogue, TPA phorbol ester, BSA-GlcNAc Neoglycoproteins with N-acetylglucosamine residues, FITC-PSA fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm, FITC-PNA fluorescein isothiocyanate-conjugated peanut agglutinin, RITC-PSA rhodamine-conjugated Pisurn sativum agglutimm
aComparison between subgroups with the Q test for heterogeneity
bNot calculated
Table 9
Summary of SMD values for induced AR assay
Subgroup
N
SMD
(95% CI)
Test(s) of heterogeneity
Significance test(s) of
SMD = 0
P a
I2 (%)
P
Z
P
 
Overall
22
0.86 (0.60–1.11)
78.7
0.000
6.55
0.000
 
Four experiments excluded
18
0.71 (0.52–0.90)
54.8
0.003
7.25
0.000
 
Geographic area
 Europe
15
0.76 (0.44–1.07)
82.1
0.000
4.68
0.000
0.001
 Oceania
1
0.66 (0.24–1.08)
b
3.10
0.002
 
 South America
1
0.97 (0.15–1.78)
2.33
0.020
 
 Africa
1
1.86 (0.91–2.80)
4.46
0.000
 
 North America
1
1.91 (1.18–2.63)
5.14
0.000
 
 Asia
3
0.86 (0.48–1.24)
0.0
0.589
4.46
0.000
 
Preparation method
 No preparation
0
      
 One preparation
22
      
  Swim up
8
1.51 (1.13–1.89)
61.3
0.012
7.75
0.000
< 0.001
  Swim up/discontinuous gradient
1
0.97 (0.15–1.78)
4.79
0.000
 
  Discontinuous gradient
13
0.47 (0.28–0.66)
48.2
0.027
2.33
0.020
 
 Double preparation
0
      
AR trigger
       
 Physiological trigger
7
0.95 (0.29–1.61)
89.1
0.000
2.81
0.005
0.92
  HFF
3
0.97 (−0.42–2.37)
95.1
0.000
1.37
0.172
 0.029
  P
3
0.65 (0.01–1.28)
73.4
0.023
1.99
0.047
 
  ZP
1
1.86 (0.91–2.80)
3.85
0.000
 
 Nonphysiological trigger
15
0.81 (0.56–1.06)
67.6
0.000
6.36
0.000
 
  A23187
10
0.87 (0.66–1.08)
26.1
0.204
8.30
0.000
< 0.001
  CAMP
1
−0.12 (−0.56–0.32)
0.54
0.588
 
  TPA
2
0.40 (0.09–0.70)
0.0
0.866
2.54
0.011
 
  BSA-GlcNAc/A23187
1
0.97 (0.15–1.78)
2.33
0.020
 
  Mannose
1
1.91 (1.18–2.63)
5.14
0.000
 
AR assay method
       
 Fluorescent labels
21
0.82 (0.57–1.08)
78.3
0.000
6.26
0.000
0.012
  Direct immunofluorescence
19
0.80 (0.52–1.07)
79.4
0.000
5.72
0.000
0.16
   With lection
12
1.16 (0.84–1.47)
66.3
0.001
7.17
0.000
< 0.001
    FITC-PSA
7
1.19 (0.68–1.71)
77.5
0.000
4.53
0.000
 0.060
    FITC-PNA
4
0.96 (0.66–1.25)
0.0
0.961
6.27
0.000
 
    RITC-PSA
1
1.91 (1.18–2.63)
7.17
0.000
 
   With antibody
7
0.28 (0.06–0.50)
44.2
0.097
2.45
0.014
 
    FITC-GB24
  Indirect immunofluorescence
2
1.11 (0.26–1.95)
64.2
0.094
2.57
0.010
 
   GB24 antibody
 Triple stain
1
1.52 (0.87–2.18)
78.7
0.000
4.57
0.000
 
Rs spearman correlation coefficient, AR acrosome reaction, CI confidence interval, HFF human follicle fluid, P progesterone, ZP zona pellucida, CAMP cyclic adenosine 3′-5′-phosphate analogue, TPA phorbol ester, BSA-GlcNAc Neoglycoproteins with N-acetylglucosamine residues, FITC-PSA fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm, FITC-PNA fluorescein isothiocyanate-conjugated peanut agglutinin, RITC-PSA rhodamine-conjugated Pisurn sativum agglutimm, FITC-GB24, fluorescein isothiocyanate-GB24
aComparison between subgroups with the Q test for heterogeneity
bNot calculated
Table 10
Summary of Summary of SEN, SPE, PLR, NLR, DS, DOR, and AUC values for induced AR assay
Subgroup
N
SEN (95% CI)
SPE (95% CI)
PLR (95% CI)
NLR (95% CI)
DS (95% CI)
DOR (95% CI)
AUC (95% CI)
P a
Overall
13
0.79 (0.71–0.85)
0.87 (0.74–0.94)
6.08 (2.77–13.36)
0.24 (0.17–0.35)
3.22 (2.19–4.24)
24.91 (8.91–69.66)
0.84 (0.81–0.87)
 
Geographic area
 Europe
5
0.80 (0.66–0.89)
0.86 (0.56–0.97)
5.80 (1.46–23.10)
0.23 (0.13–0.43)
3.21 (1.51–4.91)
24.81 (4.53–135.75)
0.86 (0.83–0.89)
NC
 Oceania
4b
0.75 (0.59–0.86)
0.77 (0.61–0.87)
3.22 (1.70–6.08)
0.33 (0.18–0.61)
2.28 (1.11–3.45)
9.78 (3.04–31.47)
0.80 (0.77–0.84)
 
 South America
1
0.78
0.91
8.56
0.24
c
35.00
 
 Africa
4b
0.94 (0.44–1.00)
0.98 (0.85–1.00)
52.54 (5.96–462.88)
0.06 (0.00–1.00)
6.76 (3.74–9.77)
861.19 (42.25–17,552.00)
0.99 (0.98–1.00)
 
 North America
4b
0.77 (0.69–0.84)
0.87 (0.64–0.96)
6.11 (1.79–20.94)
0.26 (0.16–0.41)
3.17 (1.54–4.79)
23.70 (4.68–120.00)
0.83 (0.79–0.86)
 
 Asia
1
0.82
0.70
2.77
0.26
10.75
 
Preparation method
 No preparation
1
0.71
0.55
1.58
0.53
3.00
NC
 One preparation
11
0.82 (0.73–0.88)
0.87 (0.73–0.94)
6.10 (2.84–13.09)
0.21 (0.14–0.33)
3.36 (2.32–4.39)
28.70 (10.21–80.65)
0.88 (0.85–0.91)
 
 Double preparation
1
0.63
1.00
0.40
 
AR trigger
 Physiological trigger
10b
0.82 (0.73–0.88)
0.88 (0.76–0.94)
6.78 (3.10–14.83)
0.20 (0.13–0.33)
3.50 (2.35–4.65)
32.26 (10.53–105.06)
0.89 (0.86–0.91)
NC
 Nonphysiological trigger
8
0.79 (0.70–0.85)
0.86 (0.65–0.95)
5.70 (1.98–16.39)
0.25 (0.16–0.37)
3.14 (1.82–4.46)
23.10 (6.16–81.56)
0.82 (0.78–0.85)
 
AR assay method
 Fluorescent labels
11
0.78 (0.71–0.84)
0.90 (0.78–0.96)
8.01 (3.24–19.82)
0.24 (0.18–0.34)
3.49 (2.35–4.64)
32.83 (10.44–103.21)
0.83 (0.80–0.86)
 
  Direct immunofluorescence
10
0.78 (0.70–0.85)
0.86 (0.74–0.93)
5.72 (2.81–11.63)
0.25 (0.17–0.37)
3.12 (2.11–4.14)
22.76 (8.23–62.95)
0.84 (0.81–0.87)
 
   FITC−PSA
7
0.81 (0.69–0.88)
0.83 (0.66–0.93)
4.80 (2.09–11.01)
0.23 (0.13–0.41)
3.02 (1.72–4.32)
20.51 (5.60–75.15)
0.87 (0.83–0.89)
 
   FITC−PNA
4b
0.68 (0.58–0.76)
0.85 (0.81–0.88)
4.55 (3.42–6.05)
0.38 (0.28–0.50)
2.49 (1.98–3.01)
12.10 (7.24–20.21)
0.85 (0.81–0.87)
 
   RITC−PSA
1
0.83
0.98
38.33
0.17
225.00
 
  Indirect immunofluorescence
   Anti−CD46 antibody
1
0.83
1.00
0.18
 
 Triple stain
4b
0.93 (0.76–0.98)
0.58 (0.52–0.64)
2.23 (1.96–2.54)
0.12 (0.03–0.43)
2.92 (1.59–4.25)
18.56 (4.91–70.16)
0.68 (0.64–0.72)
 
SEN sensitivity, SPE specificity, PLR positive likelihood ratio, NLR negative likelihood ratio, DS diagnostic score, DOR diagnostic odds ratio, AUC area under the summary receiver operating characteristic curve, CI confidence interval, AR acrosome reaction, FITC-PSA fluorescein isothiocyanate-conjugated Pisurn sativum agglutimm, FITC-PNA fluorescein isothiocyanate-conjugated peanut agglutinin, RITC-PSA rhodamine-conjugated Pisurn sativum agglutimm, NC not compared
aComparison between subgroups with the Q test for heterogeneity
bConverted number = actual number × 2. Studies were duplicated for numbers ≥ 2 and < 4, based on the computation of bivariate mixed effects regression model for the lowest threshold of 4 studies
cNot calculated in original data or not reported
After SEN analysis, seven studies (when pooling Rs: 3; when pooling SMD: 4) were identified as a source of heterogeneity; however, after they were excluded, the correlation was unchanged (Rs = 0.36, 95% CI: 0.24–0.47, p <  0.001; SMD = 0.71, 95% CI: 0.52–0.90, respectively) and the heterogeneity while decreased was still significant (I2 = 83.6%, p <  0.001; I2 = 54.8%, p = 0.003, respectively). There was no outlier was identified when pooling diagnostic accuracy data (Fig. 4e). Graphs of SROC curves generated indicated that the threshold effect did not apply to inter-study heterogeneity (r = − 0.146, p = 0.634; Fig. 4a).
In the subgroup analysis, datasets were stratified according to geographic area, sperm preparation method, AR trigger, and AR assay method (Tables 8, 9 and 10). The diagnostic performance in the other areas (Europe [Rs = 0.33, 95% CI: 0.11–0.55, p = 0.003; pooled moderate SEN = 0.80, 95% CI: 0.66–0.89; moderate SPE = 0.86, 95% CI: 0.56–0.97], Oceania [Rs = 0.40, 95% CI: 0.03–0.76, p = 0.035; pooled moderate SEN = 0.75, 95% CI: 0.59–0.86; moderate SPE = 0.77, 95% CI: 0.61–0.87], South America [Rs = 0.46, 95% CI: 0.17–0.75, p = 0.002; moderate SEN = 0.78, high SPE = 0.91], Asia [moderate SEN = 0.82, moderate SPE = 0.70], and North America [Rs = 0.49, 95% CI: 0.30–0.69, p < 0.001; pooled moderate SEN = 0.77, 95% CI: 0.69–0.84, moderate SPE = 0.87, 95% CI: 0.64–0.96) was inferior to that in Africa (Rs = 0.65, 95% CI: 0.05–1.25, p = 0.034; pooled high SEN = 0.94, 95% CI: 0.44–1.00, high SPE = 0.98, 95% CI: 0.85–1.00; comparison between subgroups [p] < 0.01).
No preparation (Rs = 0.39, 95% CI: 0.20–0.58, p < 0.001; moderate SEN = 0.71, low SPE = 0.55) or double preparation (Rs = 0.33, 95% CI: 0.13–0.53, p = 0.001; low SEN = 0.63, high SPE = 1.00) yielded inferior results as compared to one preparation (Rs = 0.41, 95% CI: 0.24–0.58, p < 0.001; pooled moderate SEN = 0.82, 95% CI: 0.73–0.88, moderate SPE = 0.87, 95% CI: 0.73–0.94; comparison between subgroups [p] < 0.001); discontinuous gradient (Rs = 0.17, 95% CI: 0.10–0.25, p < 0.001; SMD = 0.47, 95% CI: 0.28–0.66, p = 0.02) was inferior to swim up (Rs =0.65, 95% CI: 0.49–0.81, p < 0.001; SMD = 1.51, 95% CI: 1.13–1.89, p < 0.001; comparison between subgroups [p] < 0.001).
Nonphysiological triggers (SMD = 0.81, 95% CI: 0.56–1.06, p < 0.001; moderate SEN = 0.79, 95% CI: 0.70–0.85; pooled moderate SPE = 0.86, 95% CI: 0.65–0.95) did not differ from physiological triggers (SMD = 0.95, 95% CI: 0.29–1.61, p = 0.005; pooled moderate SEN = 0.82, 95% CI: 0.73–0.88; moderate SPE = 0.88, 95% CI: 0.76–0.94; comparison between subgroups [p] = 0.92) in general; ZP (Rs = 0.63, 95% CI: 0.25–1.01, p = 0.001; SMD = 1.86, 95% CI: 0.91–2.80, p < 0.001;) or mannose (Rs = 0.59, 95% CI: 0.42–0.76, p < 0.001; SMD = 1.91, 95% CI: 1.18–2.63, p < 0.001) was superior to other physiological (comparison between subgroups [p] < 0.05) or nonphysiological triggers (A23187 [Rs = 0.36, 95% CI: 0.13–0.58, p = 0.002; SMD = 0.87, 95% CI: 0.66–1.08, p < 0.001], BSA-GlcNAc [Rs = 0.46, 95% CI: 0.17–0.75, p = 0.002; SMD = 0.97, 95% CI: 0.15–1.78, p = 0.02]; comparison between subgroups [p] < 0.001); and there was no correlation for HFF (Rs = 0.46, 95% CI: − 0.03–0.95, p = 0.065; SMD = 0.97, 95% CI: − 0.42 − 2.37, p = 0.172), P (Rs = 0.31, 95% CI: − 0.01 − 0.63, p = 0.059), CAMP (Rs = 0.12, 95% CI: − 0.06 − 0.29, p = 0.206; SMD = − 0.12, 95% CI: − 0.56 − 0.32, p = 0.588) and TPA (Rs =0.03, 95% CI: -0.15–0.21, p = 0.773).
The diagnostic performance of fluorescent labels (Rs = 0.41, 95% CI: 0.25–0.58, p < 0.001; SMD = 0.82, 95% CI: 0.57–1.08, p < 0.001) did not differ from that of triple stain (Rs = 0.24, 95% CI: 0.03–0.45; SMD = 1.52, 95% CI: 0.87–2.18); Lower induced AR% determined by fluorescent labels or triple stain was used for predicting lower FR with pooled moderate SEN/high SPE (SEN = 0.78, 95% CI: 0.71–0.84; SPE = 0.90, 95% CI: 0.78–0.96) or pooled high SEN/low SPE (SEN = 0.93, 95% CI: 0.76–0.98; SPE = 0.58, 95% CI: 0.52–0.64). The diagnostic performance of direct immunofluorescence (Rs = 0.40, 95% CI: 0.21–0.58; SMD = 0.80, 95% CI: 0.52–1.07) did not differ from that of indirect immunofluorescence (Anti-CD46 antibdy [Rs = 0.68, 95% CI: 0.59–0.77, p < 0.001], GB24 antibody [SMD = 1.11, 95% CI: 0.26–1.95, p = 0.01]; comparison between subgroups [p] >  0.05); direct immunofluorescence with antibody (FITC-GB24: Rs = 0.15, 95% CI: 0.05–0.25, p = 0.003; SMD = 0.28, 95% CI: 0.06–0.50, p = 0.014) was inferior to direct immunofluorescence with lectin (Rs = 0.53, 95% CI: 0.36–0.70, p < 0.001; SMD = 1.16, 95% CI: 0.84–1.47, p < 0.001; comparison between subgroups < 0.001); there is no significant difference between lectins (FITC-PSA [SMD = 1.19, 95% CI: 0.68–1.71, p < 0.001], FITC-PNA [SMD = 0.96, 5% CI: 0.66–1.25, p < 0.001], and RITC-PSA [SMD = 1.91, 95% CI: 1.18–2.63, p < 0.001]; comparison between subgroups [p] = 0.06). Specifically, moderate SEN/moderate SPE (SEN = 0.81, 95% CI: 0.69–0.88; SPE = 0.83, 95% CI: 0.66–0.93), pooled low SEN/moderate SPE (SEN = 0.68, 95% CI: 0.58–0.76; SPE = 0.85, 95% CI: 0.81–0.88, and moderate SEN/high SPE (SEN = 0.83, SPE = 0.98) were obtained for FITC-PSA, FITC-PNA, and RITC-PSA.
The included studies were distributed symmetrically without obvious publication bias (Deeks’ funnel plot [p] = 0.36, Fig. 4f).

Discussion

There are many functional assays that attempt to assess the fertilization capacity of spermatozoa based on hypoosmotic swelling, peroxidative damage, acrosome status, AEs, sperm chromatin, sperm-oocyte interaction, zona pellucida binding, and zona-free oocyte penetration [65]. However, their clinical utility for diagnosing male infertility is unclear. One reliable criterion for evaluating the diagnostic performance of assays is whether or not they can predict fertilization outcomes in IVF [3, 66, 67].
Our first results showed that AE (i.e., proacrosin and acrosin) levels determined by spectrophotometry/BAPNA were positively correlated with FR. However, lower AE levels were predictive of TFF with moderate SEN but with low SPE. In addition, a meta-analysis of published literature on similar topic was performed to further expand upon the findings. To the best of our knowledge, this meta-analysis is the first study to evaluate the association between acrosome function scoring—including AE levels and AR%—and FR and the diagnostic performance of acrosome function scoring. No attempt has been made here to correlate the scoring with conception rates because several other factors, such as the endometrial secretions, receptivity and systemic and local endocrine status, become significant after embryo transfer [54]. After validating the correlation with pooling Rs and SMD, lower AE levels or induced AR% was predictive of lower FR with moderate accuracy (AUC between 0.70–0.90); this was accompanied by low SEN/moderate SPE, moderate SEN/moderate SPE, respectively. A moderate SPE indicates that a male diagnosed as scoring -negative (i.e., higher than the AE cut-off value) has about 85% or greater probability of having a high FR (i.e., higher than the FR cut-off value). Fifteen percent of the patients with high AE levels and poor fertilization probably have defects other than impaired AEs [18]. For induced AR assay, the findings were in agreement with the results of Oehninger et al. [68], who reported that AR results were predictive of IVF rates, showing moderate accuracy, SEN and SPE. However, for AE levels, a low SEN indicates that a male diagnosed as AE-positive (i.e., low than the AE cut-off value) still has a 43% probability of having a high FR. The described first results are expected as proacrosin/acrosin is an important enzyme for fertilization. However, the SPE is low, probably because its action is dependent on structural and biochemical events which take place during capacitation and the acrosome reaction and it cannot be detected in its proper location (i.e., the acrosome) like fluorometry [3]. The other kinds of AEs, such as hyaluronidase, were not taken into consideration. Furthermore, the satisfying diagnostic performance was not obtained for assays in the meta-analysis, in spite of synthesizing multiple assay methods. This result in relatively low SEN might be attributed to other parameters of sperm function, such as good membrane integrity, normal chromatin decondensation, excellent ability of undergoing capacitation and hyperactivation, high inducibility of the acrosome reaction (AR), increased sperm-oolemma interaction, or mild peroxidative damage, low DNA fragmentation. However, it should be mentioned that the fertilization process is a multifactorial process where female factors, such as young woman, maturity of oocyte/spindle/zona pellucida, intactness of cumulus-oocyte complex, or good ability to modulate/restore sperm functions, may contribute to high fertilization [15, 16]. For spontaneous AR assay, a weak correlation was obtained when pooling Rs; however, after enlarging the sample size, there was no significant correlation between them when pooling SMD. The spontaneous AR assay was considered for the evaluation of the initial acrosome stability before ZP binding; a low percentage of spontaneous AR did not seem to influence sperm fertility may due to high heterogeneity of spermatozoa.
In addition, there was notable heterogeneity when pooling summary measures in the present meta-analysis. After SEN analysis, two studies were identified as a source of heterogeneity when pooling Rs for AE assay. One reported a linear correlation between AE and the percentage of cases with ≥70% fertilization achieved by IVF [8]. On the other hand, semen prepared by α-chymoytrypsin treatment was suitable for highly viscous semen [54]. When SMD was pooled, four studies [3, 6, 50, 53] were found to contribute to this heterogeneity. Two used cryopreserved spermatozoa to assay AE [50, 53]; one used spermatozoa without preparation [6] or spermatozoa subjected to a special discontinuous gradient (i.e., 1-ml fractions of 90%, 80%, and 50% Percoll in isotonic Ham’s-F10) [3] in IVF therapy. When pooling diagnostic accuracy data, one outlier may have affected inter-study heterogeneity, for which the highest AE cut-off value was obtained by the spectrophotometry/BAPNA assay (54 μIU/106 spermatozoa) [57]. The sperm origin (fresh or cryopreserved), sperm preparation methods, FR cut-off values, and AE assay methods and cut-off values might contribute to inter-study heterogeneity. For spontaneous AR assay, three studies found to contribute to this heterogeneity when pooling SMD. Two used FITC-PSA to determine AR after incubation for 60 min in synthetic human tubal fluid (HTF) media [33, 63]; one used two-color fluorescence staining of FITC-PSA and anti-CD46 antibody (MH61) to assay acrosomal status after 4 h of incubation in mBWW/3.5% HSA media [29]. The sperm capacitation time, media, and assay methods might contribute to inter-study heterogeneity. For induced AR assay, seven studies [31, 33, 41, 43, 63] were identified as a source of heterogeneity. The inconsistencies among studies regarding capacitation time (range between 1 h and 24 h), sperm preparation methods (swim up or discontinuous gradient), AR triggers (physiological [HFF, P, ZP] or nonphysiological [TPA, CAMP, mannose]), as well as AR assay methods (FITC-PSA, RITC-PSA, FITC-GB24) methods might contribute to inter-study heterogeneity.
Furthermore, the subgroup analysis revealed that the correlation between AE levels and FR depended on geographic area, with Asia being inferior in this regard to North America and Europe, which may be explained by methodological quality. For example, two of three studies in Asia [9, 18] did not describe the inclusion criteria for patients undergoing IVF therapy, whereas only a minority of North American (i.e., three of seven) [6, 8, 19] and European (i.e., one in six articles) [3] studies did not report these criteria. In addition, two Asian studies [9, 57] did not clearly define the reference standard test (i.e., fertilization), which was only true for two North American [6, 50] and one European [54] study. Additionally, there may be racial differences that could possibly contribute, but this is unknown. The populations of certain areas of the world, such as in parts of North America, can be very heterogeneous as well and racial status cannot be assumed. In the sperm head, the organelle most affected by cryopreservation damage was the acrosome [69], suggesting that cryopreserved spermatozoa were inferior to fresh spermatozoa. Spermatozoa without preparation more closely reflected the population composition and fertility of the original ejaculate [6] and were superior to spermatozoa after swim up and a discontinuous gradient in terms of diagnostic performance. It was difficult to predict FR based on AE levels with high accuracy as well as SEN and SPE using any one assay method. The lower AE levels determined by fluorometry—including pAb-acrosin, pAb-hyaluronidase, and mAb 4D4-proacrosin—could predict TFF with low SEN and high SPE. Lower AE levels determined by the gelatine substrate assay could predict lower FR (i.e., FR ≤ 50% or <  50%) with low SEN and high SPE. As for the hyaluronidase target with agar/hyaluronic acid mixture substrate assay, the diagnostic performance was not evaluated because the described high SEN (0.91) and SPE (1.00) for predicting TFF in the text has contradiction with the calculated low SEN (0.54) and high SPE (1.00) from scatterplot of correlation between hyaluronidase activity and FR in the study by Abdul-Aziz et al. [19]. More studies are needed to determine its predictability. The spectrophotometry assay had an uncertain predictive value. Specifically, the lower AE levels determined by the most commonly used spectrophotometry/BAPNA assay could predict a FR <  70%, FR <  50%, or FR = 0%; this was accompanied by moderate SEN/moderate SPE, pooled low SEN/moderate SPE and moderate SEN/low SPE, respectively. This result also validated the finding from retrospective study. AE levels determined by Accu-Sperm spectrophotometry/BAPNA could predict TFF with low SEN and moderate SPE. However, the lower AE levels obtained by spectrophotometry/BAEE in one study were not correlated with TFF. Another study [10] that was not included in our analysis showed similar results by the same method (AE extraction with acid [i.e., pH = 2.8]) but did not reflect the actual levels of proacrosin converted to acrosin.
For induced AR assay, the diagnostic performance also showed regional effects; the Africa in this regard was superior to other areas, which may be explained by methodology or high inter-study heterogeneity in other certain areas. For example, all three studies [31, 35, 63] in Africa used the same sperm preparation method (swim up), trigger (ZP), and assay method (FITC-PSA) and clearly defined the reference standard test. Two of them executed the laboratory quality control for assay method by establishing intra- and interassay/technician coefficients of variations, but only one study in other area did [34]. The spermatozoa after one preparation—especially swim up—show better survival after incubation in capacitation media compared with no-prepared or double-prepared spermatozoa, which may explain its optimal diagnostic performance [70]. The nonphysiological triggers did not differ from physiological triggers in terms of diagnostic performance; the mannose maybe act as a substitute when lack of physiological triggers. Nevertheless, the use of human ZP, biologically active recombinant ZP3 or active, synthetic ZP3 peptides (or analogues) combined with a better understanding of the biochemistry of the carbohydrate–protein interactions that take place during gamete recognition, binding and induction of acrosomal exocytosis will undoubtedly help in their elaboration [68]. Finally, it was difficult to predict FR based on induced AR% with high accuracy as well as SEN and SPE using any one assay method. Multiple methods (i.e., indirect immunofluorescence, direct immunofluorescence with lection, and triple stain) may be combined to obtain high SEN and SPE.
In conventional IVF therapy, one of the major disappointments that infertile couples may encounter is the unexpected failure to achieve fertilization. Some researches using early rescue ICSI procedure performed 4–6 h post-insemination have described successful salvage of some total or near-total fertilization failure cycles [71, 72]. Therefore, it may provide more important clinic direction when the acrosome function assays were used for predicting TFF. For AE assay, lower AE levels determined by spectrophotometry/BAPNA, Accu-Sperm spectrophotometry/BAPNA, or fluorometry—including pAb-acrosin assay, pAb-hyaluronidase, and mAb 4D4-proacrosin—were used for predicting TFF, with moderate SEN/low SPE, low SEN/moderate SPE, or low SEN/high SPE. For induced AR assay, lower induced AR% determined by triple stain or direct immunofluorescence with lection—including FITC-PSA and FITC-PNA—was used for predicting TFF, with high SEN/low SPE and moderate SEN/moderate SPE. Based on optimal diagnostic performance, a two-method assay using AE levels determined by pAb-acrosin assay and induced AR% determined by triple stain can be recommended for assessing acrosome function and predicting TFF. Two-method assay will reveal four types of detection results: AE levels-postive (< 60% for normal fluorescence scores)/induced AR%-positive (< 31.3% for difference between induced AR minus the spontaneous AR results), AE levels-negative (≥ 60% for normal fluorescence scores)/induced AR%-negative (≥ 31.3% for difference between induced AR minus the spontaneous AR results), AE levels-positive/induced AR%-negative, and AE levels-negative/induced AR%-positive. The early rescue ICSI procedure should be recommended for the patients diagnosed as AE levels-postive/induced AR%-positive, for which has a higher chance of TFF, or patients with high-risk factors—such as unexplained infertility or primary infertility with longer infertility duration—and with conflicting diagnosis (i.e., AE levels-postive/induced AR%-negative or AE levels-negative/induced AR%-positive). The conventional IVF therapy should be recommended for the patients diagnosed as AE levels-negative/induced AR%-negative, for which has a higher chance of fertilization success, or patients with conflicting diagnosis but without high-risk factors.
Our cohort study has several limitations: First, our dataset was collected retrospectively from a single center in a single geographic area and AE was determined by a single spectrophotometric method. Second, the sample size was not large and only FR was the primary fertilization outcome. The meta-analysis results should be considered in the context of their strengths and limitations. The advantages were as follows: the pooling of multiple summary measures; SEN and subgroup analyses to identify sources of heterogeneity; and low publication bias, which confirmed the reliability of the results. Nonetheless, there were some limitations such as no available RCT; the inclusion of old articles (published between 1988 and 2014) and studies with high heterogeneity; and the omission of some AE assay methods, including acrosin/proacrosin/acrosin inhibitor [12] or hyaluronidase [13] target with BAEE substrate assay, hyaluronidase target with cytochemical [14] or hyaluronic acid substrate [2] assay; and acrosin target with western blotting [5] or RIA [20], for which articles were lacking.

Conclusions

The results of our study demonstrate that the acrosome function assays used to predict FR with high SEN and SPE are deficient. A limited prediction was obtained for AE assays, even though multiple methods (i.e., fluorometry, spectrophotometry, substrate assays) may be combined. But for induced AR assay, multiple methods (i.e., indirect immunofluorescence, direct immunofluorescence with lection, and triple stain) may be combined to obtain high SEN and SPE. The diagnostic performance showed regional effects as well as an effect of the sperm preparation or assay method. New assays of acrosome function—such as ones utilizing a panel of monoclonal or polyclonal antibodies against acrosome-related proteins—should be developed as a supplement for a more accurate diagnosis of structural and functional defects in the sperm acrosome. In addition, although most fertility centers rather prefer ICSI than IVF as method of treatment for male-factor infertility couples, yet the pace of this decision-making process should slow down, considering the controversy in the potential safety about ICSI. More studies of multicenter, large-scale, careful design and synthesizing multiple sperm functional assays and oocyte quality assays are still needed in clinical settings to better predict fertilization outcome in IVF. The early rescue ICSI procedure should be recommended for the patients with a higher chance of fertilization failure, and the conventional IVF therapy should be recommended for the patients with a higher chance of fertilization success.

Acknowledgements

We thank WebShop for its linguistic assistance with an earlier version of the manuscript.

Funding

This work was supported by National Natural Science Foundation of China (No. 31472054), The National Research Foundation for the Doctor Program of Higher Education of China (20120162110058).

Availability of data and materials

The data and materials are available from the corresponding author on reasonable requests.

Capsule

Sperm acrosome function scoring is positively correlated with fertilization rate, which is predictive of fertilization outcome with moderate accuracy and specificity.
The study was sanctioned by the ethics committee of the Reproductive and Genetic Hospital of CITIC-Xiangya. Due to the retrospective nature of the study, informed consent was waived.
Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Metadaten
Titel
Human sperm acrosome function assays are predictive of fertilization rate in vitro: a retrospective cohort study and meta-analysis
verfasst von
Fang Xu
Ganggang Guo
Wenbing Zhu
Liqing Fan
Publikationsdatum
01.12.2018
Verlag
BioMed Central
Erschienen in
Reproductive Biology and Endocrinology / Ausgabe 1/2018
Elektronische ISSN: 1477-7827
DOI
https://doi.org/10.1186/s12958-018-0398-y

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